• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.61-69
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• 2015

This study presents a probabilistic knowledge discovery method to interpret heart rate variability (HRV) based on time and frequency domain indexes, extracted using discrete wavelet transform. The knowledge induction algorithm was composed of two phases: rule generation and rule estimation. Firstly, a rule generation converts numerical attributes to intervals using ROC curve analysis and constructs a reduced ruleset by comparing consistency degree between attribute-value pairs with different decision values. Then, we estimated three measures such as rule support, confidence, and coverage to a probabilistic interpretation for each rule. To show the effectiveness of proposed model, we evaluated the statistical discriminant power of five rules (3 for atrial fibrillation, 1 for normal sinus rhythm, and 1 for both atrial fibrillation and normal sinus rhythm) generated using a data (n=58) collected from 1 channel wireless holter electrocardiogram (ECG), i.e., HeartCall$^{(R)}$, U-Heart Inc. The experimental result showed the performance of approximately 0.93 (93%) in terms of accuracy, sensitivity, specificity, and AUC measures, respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.8 no.3
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• pp.1-14
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• 1971

A relay servo, one of the nonlinear sytsems, is inherently compact compared to a linear system for an equivalent control problem. The power element or actuator is not adjusted proportionally in accordance with an error signals but rather is switched abruptly between several discrete conditions. Usually switched conditions are off, full, forward or full reverse. The relay system is a particularly simple and compact one, but probably more effort has been expended on its analysis and design than on all other systems together. Early studies in the art were made by Goldfarb, austin, Oppelt and Kochenburger on the describing function method, which can be used as an approximate check on the stability of the system. The describing function method is based on the assumption that any periodic wave could be approximated as a fundamental one in wide ranges of practical applications. A relay servo system usually operates on a limit cycle condition as the loop gain increases. The stability analysis compensation or any improvement effort based on the describing function method sometimes may present considerable discrepancies on physically realized practical systems. An approach to exact periodic solutions of a relay servo system is much important for the analysis, design and system improvement. This paper dells with periodic solutions of a relay servo system on the basis of describing function and generalized chopper wave form which is composed of infinite number of harmonic series. Various ways of graphical representation were attempted to get periodic solutions, some of which have shown its validity in rapid approach to exact solutions and also in judgement of system behavior.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.3
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• pp.48-55
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• 1999

Ths paper presents an optimization method which determines locations and size of capacitors simultaneously while minimizing power losses and improving voltage profile in radial distribution systems. Especially, the cost function associated with capacitor pla.cerrent is considered as step function due to banks of standard discrete capacities. Genetic algorithms(GA) are used to obtain efficiently the solution of the cost function associated with capacitors which is non-continuous and non-differentiable function. The strings in GA consist of the node nwnber index and size of capacitors to be installed. The length mutation operator, which is able to change the length of strings in each generation, is used. The proposed Jrethod which determines locations and size of capacitors simultaneously can reduce power losses and improve voltage proftle with capacitors of minimum size. Its efficiency is proved through the arolication in radial distribution systems.ystems.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1659-1663
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• 1991

A new control design methodology is presented here which is based on a nonlinear time-series reference model. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible a.c. transmission system (FACTS) with series capacitor power feedback control is studied. A bilinear auto-regressive moving average (BARMA) reference model is identified from system data and the feedback control manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index (J). A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack. These applications are typical of the numerous plants for which nonlinear adaptive control has the potential to provide significant performance improvements. For aircraft control, significant maneuverability gains can provide safer transportation under large windshear disturbances as well as tactical advantages. For FACTS, there is the potential for significant increase in admissible electric power transmission over available transmission lines along with energy conservation. Electric power systems are inherently nonlinear for significant transient variations from synchronism such as may result for large fault disturbances. In such cases, traditional linear controllers may not stabilize the swing (in rotor angle) without inefficient energy wasting strategies to shed loads, etc. Fortunately, the advent of power electronics (e.g., high-speed thyristors) admits the possibility of adaptive control by means of FACTS. Line admittance manipulation seems to be an effective means to achieve stabilization and high efficiency for such FACTS. This results in parametric (or multiplicative) control of a highly nonlinear plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.718-723
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• 2008

Bearing is one of the important mechanical elements used in various industrial equipments. Most of failures occurred during the equipment operation result from bearing defects and breakages. Therefore, monitoring of bearings is essential in preventing equipment breakdowns and reducing unexpected loss. The purpose of this paper is to present an online monitoring method to predict bearing states using vibration signals. Bearing vibrations, which are collected as a form of profile signal, are first analyzed by a discrete wavelet transform. Next, some statistical features are obtained from the resultant wavelet coefficients. In order to select significant ones among them, analysis of variance (ANOVA) is employed in this paper. Statistical features screened in this way are used as input variables to support vector machine (SVM). An hierarchical SVM tree is proposed for dealing with multi-class problems. The result of numerical experiments shows that the proposed SVM tree has a competent performance for classifying bearing fault states.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.33-40
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• 2017

In this Paper, Analyse the Steady State Behavior of TCP and TFRC with Packet Error when both TCP and TFRC Flows Co-exist in the Network. First, Model the Network with TCP and TFRC Connections as a Discrete Time System. Second, Calculate Average Round Trip Time of the Packet Between Source and Destination on Packet Loss Environment. Then Derive the Steady State Performance i.e. Throughput of TCP and TFRC, and Average Buffer Size of RED Router Based on the Analytic Network Model. The Throughput of TCP and TFRC Connection Decrease Rapidly with the Growth of Sending Window Size and Their Transmission Rate but Their Declines become Smoothly when the Number of Sending Window Arrives on Threshold Value. The Average Queue Length of RED Router Increases Slowly on Low Transmission Rate but Increases Rapidly on High Transmission Rate.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.17-24
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• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.197-203
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• 2005

In this paper, we propose an emotion recognition using facial Images to effectively design human interface. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition for the facial images is performed after applying the discrete wavelet. Here, the feature vectors are extracted from the PCA and LDA. Experimental results show that human emotions such as happiness, sadness, and anger has better performance than surprise, fear and dislike. Expecially, Japanese shows lower performance for the dislike emotion. Generally, the recognition rates for Korean have higher values than Japanese cases.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.431-437
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• 2004

This paper propose a facial recognition method based on an ubiquitous computing that is one of next generation intelligence technology fields. The facial images are acquired by a mobile device so-called cellular phone camera. We consider a mobile security using facial feature extraction and recognition process. Facial recognition is performed by the PCA and fuzzy LDA algorithm. Applying the discrete wavelet based on multi-resolution analysis, we compress the image data for mobile system environment. Euclidean metric is applied to measure the similarity among acquired features and then obtain the recognition rate. Finally we use the mobile equipment to show the efficiency of method. From various experiments, we find that our proposed method shows better results, even though the resolution of mobile camera is lower than conventional camera.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.